AI Evaluation, Without the Engineering Tax
Find the best LLM for your use case.Without writing code.
Bring your prompts, documents, and datasets. Vyoma compares the models, tunes the RAG setup, scores the answers, and shows the full cost of every run. No SDK. No instrumentation. Your data is scored, then dropped, with open-source judges hosted by Vyoma or run privately when needed.
The leaderboard is not your use case.
The first wave of AI was “use GPT-4 for everything.” That bill is now arriving.
Teams are asking the question their CFO is forcing on them: do we actually need a frontier model for our support tickets? For our RAG? For our internal search?
Most don't. But nobody has a serious way to find out — until now.
What Vyoma does
Compare, tune, score, and price every run.
Compare.
Every major frontier model and the open-source models worth running, side by side. On your prompts. On your data.
Tune your RAG, live.
Plug in your documents. Pick your embedding model. Pick the LLM that does the generation. Change either one in real time and watch accuracy, latency, and cost update side by side. No vector DB setup. No retrieval code. No re-indexing scripts.
Track every penny.
Input tokens, output tokens, hidden reasoning tokens, judge tokens, embedding tokens — and the dollar figure on every run. The "surprise bill" doesn't happen here.
Score it the way your domain demands.
Accuracy. Faithfulness. Citation correctness. Reasoning soundness. Pick the metrics that matter for your work, or start from one of our pre-built rubrics for RAG, agents, summarization, and Q&A.
How Vyoma is different
No SDK. No model bias. No data dragnet.
No SDK in your code. No instrumentation. No “talk to engineering first.”
Every other eval tool on the market asks you to install a library, decorate your LLM calls, and ship code to production. Vyoma is a UI — you click, you compare, you decide. The PM who owns the bill can use it. The domain expert who actually knows the right answer can use it. Engineering is no longer the gate.
Neutral across providers, by design.
Vyoma doesn't host generation models. We federate — OpenAI, Anthropic, Google, Groq, DeepInfra, Together, Fireworks, your own VPC, or Ollama on your laptop. We have no incentive to push you toward any model. The cheapest one that's good enough for your task wins.
Your data never trains anything. Promise — architectural, not legal.
When you run an eval, your prompts and outputs transit Vyoma to be scored, then they're dropped. Nothing stored. Nothing logged. Nothing trained on. The judges are open-source models we host ourselves, so no third party ever sees your data. Working with regulated or sensitive data? Run the judge on your own infra in one click — local Ollama, your own API key, or a private deployment.
Built for everyone
Start in the UI. Scale into code later.
Today
For the people who actually need to decide.
Product managers, domain experts, AI consultants, small teams. The UI does the whole job. No code. No setup beyond bringing your data.
Coming
For engineering teams that want to wire it into CI.
A thin SDK and CLI for triggering Vyoma evals from your pipelines, ingesting recommendations into your model router, and gating deploys on quality metrics. Same backend, different surface. Watch for it as we approach v1.0.
Be early
Help shape Vyoma v0.1.
Vyoma v0.1 launches August 2026. Early signups get founder-led setup, help building their first eval, and a direct line into what we ship next.